The current paper investigates the possibility of establishing an empirically based model for predicting the emission rate of nitrogen oxides (NO x ) from oil refinery furnaces, in order to continually track emissions with respect to environmental licence limits. Model input data were collected by direct stack monitoring using an electrochemical cell NO x analyser, as well as a range of telemetry sensors to obtain refinery process parameters. Principal Component Analysis (PCA), in conjunction with Partial Least Squares (PLS) regression was then used to build a series of models able to predict NO x emissions from the furnaces. The models produced were proven to be robust, with a relatively high accuracy, and are able to predict NO x levels over the range of operating conditions which were sampled. It was found that due to structural/operational variations a separate model is usually required for each furnace. The models can be integrated with the refinery operating system to predict NO x emission rates on a continuous basis. Two models representing structurally different furnaces are considered in this paper.